BACKGROUND: Diabetes mellitus (DM) is a serious, chronic condition affecting 2.3 million people in the UK and consuming over 5% of the total National Health Service (NHS) budget. The World Health Organization (WHO) has produced a classification of diabetes which should help ensure consistent diagnosis and management of cases. However, recent quality based targets for diabetes in the UK only allow for people with Type 1 or Type 2 diabetes to be included in the disease register. OBJECTIVE: To analyse the codes offered when recording a diagnosis of diabetes in an electronic patient record (EPR) system and to assess what proportion of existing codes would map to known diagnostic categories. METHOD: Code-sets (4-byte, 5-byte, CTv3 and SNOMED-CT) were sourced using the NHS Triset Browser and the SNOMED-CT website. We analysed the variation in child codes listed under 'diabetes mellitus'. Picking lists were generated across four general practices, using eight search terms. We examined list length and the types of codes offered. An attempt was also made to map current codes to the WHO classification of diabetes, defining each as having a 'direct mapping', a 'possible mapping', or 'no clear mapping'. RESULTS: SNOMED-CT provided a more concise list of codes (115) than the more widely used 5-byte code-set (177). There was considerable variation in the codes offered in picking lists, with variation occurring between systems, rather than between individual GP practices. In considering the potential for mapping between current code-sets and the WHO classification, there was a general downward trend in the number that had 'no clear mapping' (5-byte Read codes--46.3%, SNOMED-CT--19.1%). CONCLUSION: There is considerable variation in the different diabetic coding hierarchies and in the choices offered at the point of coding in an EPR system. This is likely to lead to inconsistent data recording. Migrating GP computer systems to SNOMED-CT or to another more limited coding system which would map to international disease classifications would enable primary care EPR systems to better support improved standards of care.
BACKGROUND:Diabetes mellitus (DM) is a serious, chronic condition affecting 2.3 million people in the UK and consuming over 5% of the total National Health Service (NHS) budget. The World Health Organization (WHO) has produced a classification of diabetes which should help ensure consistent diagnosis and management of cases. However, recent quality based targets for diabetes in the UK only allow for people with Type 1 or Type 2 diabetes to be included in the disease register. OBJECTIVE: To analyse the codes offered when recording a diagnosis of diabetes in an electronic patient record (EPR) system and to assess what proportion of existing codes would map to known diagnostic categories. METHOD: Code-sets (4-byte, 5-byte, CTv3 and SNOMED-CT) were sourced using the NHS Triset Browser and the SNOMED-CT website. We analysed the variation in child codes listed under 'diabetes mellitus'. Picking lists were generated across four general practices, using eight search terms. We examined list length and the types of codes offered. An attempt was also made to map current codes to the WHO classification of diabetes, defining each as having a 'direct mapping', a 'possible mapping', or 'no clear mapping'. RESULTS: SNOMED-CT provided a more concise list of codes (115) than the more widely used 5-byte code-set (177). There was considerable variation in the codes offered in picking lists, with variation occurring between systems, rather than between individual GP practices. In considering the potential for mapping between current code-sets and the WHO classification, there was a general downward trend in the number that had 'no clear mapping' (5-byte Read codes--46.3%, SNOMED-CT--19.1%). CONCLUSION: There is considerable variation in the different diabetic coding hierarchies and in the choices offered at the point of coding in an EPR system. This is likely to lead to inconsistent data recording. Migrating GP computer systems to SNOMED-CT or to another more limited coding system which would map to international disease classifications would enable primary care EPR systems to better support improved standards of care.
Authors: Simon de Lusignan; Stacy Shinneman; Ivelina Yonova; Jeremy van Vlymen; Alex J Elliot; Frederick Bolton; Gillian E Smith; Sarah O'Brien Journal: JMIR Med Inform Date: 2017-09-28
Authors: Simon de Lusignan; Ana Correa; Richard Pebody; Ivelina Yonova; Gillian Smith; Rachel Byford; Sameera Rankiri Pathirannehelage; Christopher McGee; Alex J Elliot; Mariya Hriskova; Filipa Im Ferreira; Imran Rafi; Simon Jones Journal: JMIR Public Health Surveill Date: 2018-04-30
Authors: Simon de Lusignan; Jamie Lopez Bernal; Maria Zambon; Oluwafunmi Akinyemi; Gayatri Amirthalingam; Nick Andrews; Ray Borrow; Rachel Byford; André Charlett; Gavin Dabrera; Joanna Ellis; Alex J Elliot; Michael Feher; Filipa Ferreira; Else Krajenbrink; Jonathan Leach; Ezra Linley; Harshana Liyanage; Cecilia Okusi; Mary Ramsay; Gillian Smith; Julian Sherlock; Nicholas Thomas; Manasa Tripathy; John Williams; Gary Howsam; Mark Joy; Richard Hobbs Journal: JMIR Public Health Surveill Date: 2020-04-02
Authors: Dylan McGagh; Simon de Lusignan; Harshana Liyanage; Bhautesh Dinesh Jani; Jorgen Bauwens; Rachel Byford; Dai Evans; Tom Fahey; Trisha Greenhalgh; Nicholas Jones; Frances S Mair; Cecilia Okusi; Vaishnavi Parimalanathan; Jill P Pell; Julian Sherlock; Oscar Tamburis; Manasa Tripathy; Filipa Ferreira; John Williams; F D Richard Hobbs Journal: JMIR Public Health Surveill Date: 2020-11-17